MBA (GLIM), Certified Supply Chain Professional (CSCP) from Association of Operations Management (APICS), Lean Six Sigma Professional (KPMG), B.E.-Marine (D.M.E.T./ M.E.R.I.)

Results (Conjoint Analysis- Indian Insurance Industry)

Posted by admin     Category: Analytics and Consulting, Business Analytics, Conjoint Analysis, Primary Research

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Results – (Conjoint Analysis of the Indian Life Insurance)

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Utility Values of Different Levels in every Factor:

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Factor

Level

Utility Estimate

Std. Error

Type

Term

.356

.191

ULIP

-.402

.191

Endowment

.046

.229

Coverage

Only Life

.019

.210

Life + heath

-.266

.260

life + pension

.704

.260

joint (spouse/ kids)

-.456

.260

Distribution

Online Purchase

.110

.191

Through Agent

.378

.191

Through Corpoate Tie-Ups

-.488

.229

Communication

Social Media

.090

.275

TV Ads

.500

.275

Newspaper & Print Ads

-.255

.275

Hoarding & Banners

.385

.275

Online Ads i.e. Google Adwords

-.720

.275

Positioning

Simple and honest plan

.412

.210

Maximizing Returns

-.217

.260

Maximizing coverage options

-.272

.260

Assured/ easier claims

.077

.260

(Constant)

12.825

.163

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Importance of Different Attributes of a Life Insurance Product:

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Relative Importance of Different Attrinutes of a life Insurance Product

Relative Importance of Different Attributes of a life Insurance Product

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Importance Values

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Type

16.160

Coverage

24.747

Distribution

18.453

Communication

26.027

Positioning

14.613

Averaged Importance Score

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Perception Scores (Utilities) of Different Plan Types:

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Utility of Different Plan Types

Perception Scores (Relative Utility) of Different Plan Types

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Explanation of Results:

This shows that the Term insurance plan is valued more by the customer then Endowment and last ULIP. The results can be interpreted by understanding the pain points Term insurance plan addresses:

  1. Lower premium costs
  2. Easier claim processing
  3. Low overhead charges

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Perception Scores (Utilities) of Different Coverage Options:

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Perception (Utility) Score of Different Coverage Options

Perception (Utility) Score of Different Coverage Options

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Explanation of Results:

The most favored distribution channel is Agent, followed by Online purchase. This highlights the increasing comfort levels with the online medium.

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Importance of Different Distribution Channels for a Life Insurance Product:

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Perception (Utility) Scores of Different Distribution Channels for a Life Insurance Product

Perception (Utility) Scores of Different Distribution Channels for a Life Insurance Product

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Explanation of Results:

The most favored distribution channel is Agent, followed by Online purchase. This highlights the increasing comfort levels with the online medium.

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Importance of Different Communication/ Advertising Channels for a Life Insurance Product:

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Perception (Utility) Scores for Different Communication/ Advertiting Channels

Perception (Utility) Scores for Different Communication/ Advertising Channels

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Explanation of Results:

TV ads still remain the most popular medium, followed by Hoarding & banners.

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Importance of Different Positioning Strategies for a Life Insurance Product:

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Perception (Utility) Scores for Different Positioning Strategies

Perception (Utility) Scores for Different Positioning Strategies

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Explanation of Results:

Simple & honest plan is the most successful positioning strategy. This shows the value consumers place on the transparency of the plan.

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<— Previous (Research 3 – Conjoint Analysis)

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<——– Return to Home (Introduction – A Conjoint Analysis of the Indian Life Insurance Industry)

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Utilities

Utility Estimate

Std. Error

Type

Term

.356

.191

ULIP

-.402

.191

Endowment

.046

.229

Coverage

Only Life

.019

.210

Life + heath

-.266

.260

life + pension

.704

.260

joint (spouse/ kids)

-.456

.260

Distribution

Online Purchase

.110

.191

Through Agent

.378

.191

Through Corpoate Tie-Ups

-.488

.229

Communication

Social Media

.090

.275

TV Ads

.500

.275

Newspaper & Print Ads

-.255

.275

Hoarding & Banners

.385

.275

Online Ads i.e. Google Adwords

-.720

.275

Positioning

Simple and honest plan

.412

.210

Maximizing Returns

-.217

.260

Maximizing coverage options

-.272

.260

Assured/ easier claims

.077

.260

(Constant)

12.825

.163

Phase 2 – Quantitaive Research (Conjoint – Indian Insurance Industry)

Posted by admin     Category: Analytics and Consulting, Business Analytics, Conjoint Analysis, Primary Research

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Phase 2 – Quantitative Research – (Conjoint Analysis of the Indian Life Insurance)

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Research 3:

Method:  Conjoint Analysis.

Type: Fractional Factorial Design/ Full Profile Conjoint Design.

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(Green, P. and Srinivasan, V. (1978) Conjoint analysis in consumer research: Issues and outlook, Journal of Consumer Research, vol 5, September 1978, pp 103-123)

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Research Design:

  • A total of 29 PLAN CARDS (25 test cards and 4 hold out cards), were obtained using the ORTHOGONAL ARRAY Design.

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Factors and Levels:

  • Based on our Qualitative research we used the following factors, with the given levels.

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Factor 1: Type of Policy

Levels:
  1. TERM Plan
  2. ULIP
  3. Endowment

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Factor 2: Coverage/ features/ riders

Levels:
  1. Plain Life Insurance Plan
  2. Life Insurance with Health Cover
  3. Life Insurance with Pension Cover
  4. Joint Life Insurance Plan (for Spouse/ Kid’s education)

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Factor 3: Distribution Channel

Levels:
  1. Online Purchase
  2. Assisted by Insurance Agent
  3. Through Corporate Tie-Ups

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Factor 4: Integrated Communication Channel

Levels:
  1. Social Media (Blogs, Twitter, Facebook, Expert/ peer reviews etc.)
  2. Online Ads on related sites (like google adwords)
  3. TV and conventional digital media
  4. Newspapers and other Print Media
  5. Banners and Hoardings

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Factor 5: Positioning Strategy

Levels:
  1. Easy, Hassle Free, Convenient, Honest
  2. Maximizing  Returns/ Savings for the future needs
  3. Maximum coverage and features (as in medical claims, and other contingencies)
  4. Easier and faster Claim Processing and Maximum Assurance.

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Sampling:

  • We took a stratified random sample of 45 respondents of age group between 20-30 years with varying educational levels, profession, gender, and domicile.
  • The above sample ensured a degree of error of less than 10% at 95% confidence level in the conjoint research methodology.
  • The respondents were explained the research methodology and the use of Plan Cards as used in the study.
  • NO monetary compensations were offered, and the unbiased, voluntary co-operation was ensured throughout.

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Methodology:

  • Using SPSS 17, 29 Plan Cards (25 (25 test cards and 4 hold out cards), were obtained using the ORTHOGONAL ARRAY Design.
  • The respondents were asked to rank these options (plan cards), according to their willingness to buy.
  • Besides the plan cards, some demographical (age, gender, domicile, profession, education data was also collected that could be further used for segmentation and profiling purposes.
  • A facilitator educated in conjoint methodology was stationed to help the respondents, and ensure good quality of data.
  • After collecting all the responses the same were entered back in SPSS, and the results obtained and tabulated.

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<— Previous (Design of Experiment)

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<——– Return to Home (Introduction – A Conjoint Analysis of the Indian Life Insurance Industry)

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Next (Result – Conjoint – Indian Insurance) —>

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